Association mapping and genetic dissection of drought-induced canopy temperature differences in rice

Uncovering the Genomic Regions Associated with Yield Maintenance in Rice Under Drought Stress Using an Integrated Meta-Analysis Approach

The complex trait of yield is controlled by several quantitative trait loci (QTLs). Given the global water deficit issue, the development of rice varieties suitable for non-flooded cultivation holds significant importance in breeding programs. The powerful approach of Meta-QTL (MQTL) analysis can be used for the genetic dissection of complicated quantitative traits. In the current study, a comprehensive MQTL analysis was conducted to identify consistent QTL regions associated with drought tolerance and yield-related traits under water deficit conditions in rice. In total, 1087 QTLs from 134 rice populations, published between 2000 to 2021, were utilized in the analysis. Distinct MQTL analysis of the relevant traits resulted in the identification of 213 stable MQTLs. The confidence interval (CI) for the detected MQTLs was between 0.12 and 19.7 cM. The average CI of the identified MQTLs (4.68 cM) was 2.74 times narrower compared to the average CI of the initial QTLs. Interestingly, 63 MQTLs coincided with SNP peak positions detected by genome-wide association studies for yield and drought tolerance-associated traits under water deficit conditions in rice. Considering the genes located both in the QTL-overview peaks and the SNP peak positions, 19 novel candidate genes were introduced, which are associated with drought response index, plant height, panicle number, biomass, and grain yield. Moreover, an inclusive MQTL analysis was performed on all the traits to obtain "Breeding MQTLs". This analysis resulted in the identification of 96 MQTLs with a CI ranging from 0.01 to 9.0 cM. The mean CI of the obtained MQTLs (2.33 cM) was 4.66 times less than the mean CI of the original QTLs. Thirteen MQTLs fulfilling the criteria of having more than 10 initial QTLs, CI < 1 cM, and an average phenotypic variance explained greater than 10%, were designated as "Breeding MQTLs". These findings hold promise for assisting breeders in enhancing rice yield under drought stress conditions.

Pyramiding of qDTY1.1 and qDTY3.1 into rice mega-variety Samba Mahsuri-Sub1: physiological performance under water deficit conditions

Water deficit is a crucial factor causing huge loss to rice productivity. The present study aimed to develop a multiple stress tolerant genotype by pyramiding drought tolerant yield QTLs qDTY1.1 and qDTY3.1 into high yielding rice variety Samba Mahsuri Sub-1(SMS) through marker assisted pyramiding. To achieve this six introgression lines of SMS carrying qDTY1.1 (SAB) were crossed with DRR-50, an Essentially Derived Variety of SMS carrying qDTY3.1. The SAB lines are taller than SMS due to tight linkage between qDTY1.1 and wild type SD-1. Therefore, F2 generation of crosses were screened for recombinants between SD-1 and qDTY1.1. Phenotyping of 1530 F2 plants representing three F2 populations from 35 F1 hybrids, identified 305 dwarf plants. Three dwarf F2 plants along with three others carrying qDTY1.1 and qDTY3.1 were forwarded to F3 generation. From the six F3 (SABD) lines fourteen pyramided progenies were selected and forward to F4 generation. The six SABD F3 lines SABD-7, SABD-8, SABD-9, SABD-76, SABD-79 and SABD-80 along with parents were evaluated under moisture stress (MS) for various physiological parameters. Chlorophyll and relative water content were more, while canopy temperature and malonaldehyde (MDA) content were lesser in SABD lines compared to parents indicating tolerance under MS. Variance due to genotypes was highly significant for all the yield related traits except test weight. Based on seed morphology, agronomic characters and physiological parameters six superior lines SABD-9-3, SABD-9-2, SABD-9-6, SABD-9-7, SABD-76-2 and SABD-76-6 performing better under MS were identified, which could be released after multi-location evaluation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-023-01387-5.

Monitoring of drought stress and transpiration rate using proximal thermal and hyperspectral imaging in an indoor automated plant phenotyping platform

BACKGROUND

Thermography is a popular tool to assess plant water-use behavior, as plant temperature is influenced by transpiration rate, and is commonly used in field experiments to detect plant water deficit. Its application in indoor automated phenotyping platforms is still limited and mainly focuses on differences in plant temperature between genotypes or treatments, instead of estimating stomatal conductance or transpiration rate. In this study, the transferability of commonly used thermography analysis protocols from the field to greenhouse phenotyping platforms was evaluated. In addition, the added value of combining thermal infrared (TIR) with hyperspectral imaging to monitor drought effects on plant transpiration rate (E) was evaluated.

RESULTS

The sensitivity of commonly used TIR indices to detect drought-induced and genotypic differences in water status was investigated in eight maize inbred lines in the automated phenotyping platform PHENOVISION. Indices that normalized plant temperature for vapor pressure deficit and/or air temperature at the time of imaging were most sensitive to drought and could detect genotypic differences in the plants' water-use behavior. However, these indices were not strongly correlated to stomatal conductance and E. The canopy temperature depression index, the crop water stress index and the simplified stomatal conductance index were more suitable to monitor these traits, and were consequently used to develop empirical E prediction models by combining them with hyperspectral indices and/or environmental variables. Different modeling strategies were evaluated, including single index-based, machine learning and mechanistic models. Model comparison showed that combining multiple TIR indices in a random forest model can improve E prediction accuracy, and that the contribution of the hyperspectral data is limited when multiple indices are used. However, the empirical models trained on one genotype were not transferable to all eight inbred lines.

CONCLUSION

Overall, this study demonstrates that existing TIR indices can be used to monitor drought stress and develop E prediction models in an indoor setup, as long as the indices normalize plant temperature for ambient air temperature or relative humidity.

Thermal imaging: The digital eye facilitates high-throughput phenotyping traits of plant growth and stress responses

Plant phenotyping is important for plants to cope with environmental changes and ensure plant health. Imaging techniques are perceived as the most critical and reliable tools for studying plant phenotypes. Thermal imaging has opened up new opportunities for nondestructive imaging of plant phenotyping. However, a comprehensive summary of thermal imaging in plant phenotyping is still lacking. Here we discuss the progress and future prospects of thermal imaging for assessing plant growth and stress responses. First, we classify thermal imaging into ground-based and aerial platforms based on their adaptability to different experimental environments (including laboratory, greenhouse, and field). It is convenient to collect phenotypic information of different dimensions. Second, in order to enhance the efficiency of thermal image processing, automatic algorithms based on deep learning are employed instead of traditional manual methods, greatly reducing the time cost of experiments. Considering its ease of implementation, handling and instant response, thermal imaging has been widely used in research on environmental stress, crop yield, and seed vigor. We have found that thermal imaging can detect thermal energy dissipation caused by living organisms (e.g., pests, viruses, bacteria, fungi, and oomycetes), enabling early disease diagnosis. It also recognizes changes leaf surface temperatures resulting from reduced transpiration rates caused by nutrient deficiency, drought, salinity, or freezing. Furthermore, thermal imaging predicts crop yield under different water states and forecasts the viability of dormant seeds after water absorption by monitoring temperature changes in the seeds. This work will assist biologists and agronomists in studying plant phenotypes and serve a guide for breeders to develop high-yielding, stress-tolerant, and superior crops.

QTLs and Candidate Loci Associated with Drought Tolerance Traits of Kaybonnet x ZHE733 Recombinant Inbred Lines Rice Population

Rice is the most important staple crop for the sustenance of the world's population, and drought is a major factor limiting rice production. Quantitative trait locus (QTL) analysis of drought-resistance-related traits was conducted on a recombinant inbred line (RIL) population derived from the self-fed progeny of a cross between the drought-resistant tropical japonica U.S. adapted cultivar Kaybonnet and the drought-sensitive indica cultivar ZHE733. K/Z RIL population of 198 lines was screened in the field at Fayetteville (AR) for three consecutive years under controlled drought stress (DS) and well-watered (WW) treatment during the reproductive stage. The effects of DS were quantified by measuring morphological traits, grain yield components, and root architectural traits. A QTL analysis using a set of 4133 single nucleotide polymorphism (SNP) markers and the QTL IciMapping identified 41 QTLs and 184 candidate genes for drought-related traits within the DR-QTL regions. RT-qPCR in parental lines was used to confirm the putative candidate genes. The comparison between the drought-resistant parent (Kaybonnet) and the drought-sensitive parent (ZHE733) under DS conditions revealed that the gene expression of 15 candidate DR genes with known annotations and two candidate DR genes with unknown annotations within the DR-QTL regions was up-regulated in the drought-resistant parent (Kaybonnet). The outcomes of this research provide essential information that can be utilized in developing drought-resistant rice cultivars that have higher productivity when DS conditions are prevalent.

Genetic Mapping of the Root Mycobiota in Rice and its Role in Drought Tolerance

BACKGROUND

Rice is the second most produced crop worldwide, but is highly susceptible to drought. Micro-organisms can potentially alleviate the effects of drought. The aim of the present study was to unravel the genetic factors involved in the rice-microbe interaction, and whether genetics play a role in rice drought tolerance. For this purpose, the composition of the root mycobiota was characterized in 296 rice accessions (Oryza sativa L. subsp. indica) under control and drought conditions. Genome wide association mapping (GWAS) resulted in the identification of ten significant (LOD > 4) single nucleotide polymorphisms (SNPs) associated with six root-associated fungi: Ceratosphaeria spp., Cladosporium spp., Boudiera spp., Chaetomium spp., and with a few fungi from the Rhizophydiales order. Four SNPs associated with fungi-mediated drought tolerance were also found. Genes located around those SNPs, such as a DEFENSIN-LIKE (DEFL) protein, EXOCYST TETHERING COMPLEX (EXO70), RAPID ALKALINIZATION FACTOR-LIKE (RALFL) protein, peroxidase and xylosyltransferase, have been shown to be involved in pathogen defense, abiotic stress responses and cell wall remodeling processes. Our study shows that rice genetics affects the recruitment of fungi, and that some fungi affect yield under drought. We identified candidate target genes for breeding to improve rice-fungal interactions and hence drought tolerance.

Low canopy temperature and high stomatal conductance contribute to high grain yield of contrasting japonica rice under aerobic conditions

Water limitation is a major concern in rice production. It has been suggested that with adapted genotypes, aerobic rice production offers the maintenance of grain yield while saving water. However, there has been limited exploration of japonica germplasm adapted for high-yield aerobic environments. Therefore, three aerobic field experiments with different levels of relatively high-water availability were conducted across two seasons to explore genetic variation in grain yield and physiological traits that contributed to high yield. In the first season, a japonica rice diversity set was explored under well-watered (WW20) conditions. While in the second season, a well-watered (WW21) experiment and an intermittent water deficit (IWD21) experiment were conducted to examine the performance of a subset of 38 genotypes selected for low (mean of -6.01°C) and high (mean of -8.22°C) canopy temperature depression (CTD). In WW20, CTD explained 19% of the variation in grain yield which was similar to the variation explained by plant height, lodging, and leaf death response to heat. In WW21, a relatively high average grain yield (9.09 t ha^-1) was achieved, while a 31% reduction was achieved in IWD21. Compared with the low CTD group, the high CTD group had 21% and 28% higher stomatal conductance, 32% and 66% higher photosynthetic rate, and 17% and 29% higher grain yield in the WW21 and IWD21, respectively. This work demonstrated the advantage of higher stomatal conductance and cooler canopy temperature which resulted in higher photosynthetic rate and higher grain yield. Two promising genotypes with high grain yield, cooler canopy temperature, and high stomatal conductance were identified as donor genotypes for use by the rice breeding program when aerobic rice production is a target. Field screening for cooler canopies within a breeding program with high-throughput phenotyping tools would be of value for genotype selection for aerobic adaption.

Disentangling the Roles of Plant Water Status and Stem Carbohydrate Remobilization on Rice Harvest Index Under Drought

BACKGROUND

Harvest index is an important component of grain yield and is typically reduced by reproductive stage drought stress in rice. Multiple drought response mechanisms can affect harvest index including plant water status and the degree of stem carbohydrate mobilization during grain filling. In this study, we aimed to dissect the contributions of plant water status and stem carbohydrate mobilization to harvest index. Pairs of genotypes selected for contrasting harvest index but similar biomass and days to flowering were characterized at ICAR-RCER, Patna, India and at IRRI, Philippines.

RESULTS

Multiple traits were related with harvest index across experiments, including mobilization efficiency at both sites as indicated by groupings in principal component analysis, and plant water status as indicated by direct correlations. Biomass-related traits were positively correlated with harvest index at IRRI but biomass was negatively correlated with harvest index at ICER-RCER, Patna. We observed that some pairs of genotypes showed differences in harvest index across environments, whereas other showed differences in harvest index only under drought. Of all time points measured when all genotypes were considered together, the stem carbohydrate levels at maturity were most consistently (negatively) correlated with harvest index under drought, but not under well-watered conditions. However, in the pairs of genotypes grouped as those whose differences in harvest index were stable across environments, improved plant water status resulted in a greater ability to both accumulate and remobilize stored carbohydrate, i.e. starch.

CONCLUSION

By distinguishing between genotypes whose harvest index was improved across conditions as opposed to specifically under drought, we can attribute the mechanisms behind the stable high-harvest index genotypes to be more related to stem carbohydrate remobilization than to plant water status. The stable high-harvest index lines in this study (Aus 257 and Wanni Dahanala) may confer mechanisms to improve harvest index that are independent of drought response and therefore may be useful for breeding improved rice varieties.

Genome-wide discovery of genetic variations between rice cultivars with contrasting drought stress response and their potential functional relevance

Drought stress is a serious threat to rice productivity. Investigating genetic variations between drought-tolerant (DT) and drought-sensitive (DS) rice cultivars may decipher the candidate genes/regulatory regions involved in drought stress tolerance/response. In this study, whole-genome resequencing data of four DS and five DT rice cultivars were analyzed. We identified a total of approximately 4.8 million single nucleotide polymorphisms (SNPs) and 0.54 million insertions/deletions (InDels). The genetic variations (162,638 SNPs and 17,217 InDels) differentiating DS and DT rice cultivars were found to be unevenly distributed throughout the rice genome; however, they were more frequent near the transcription start and stop sites than in the genic regions. The cis-regulatory motifs representing the binding sites of stress-related transcription factors (MYB, HB, bZIP, ERF, ARR, and AREB) harboring the SNPs/InDels in the promoter regions of a few differentially expressed genes (DEGs) were identified. Importantly, many of these DEGs were located within the drought-associated quantitative trait loci. Overall, this study provides a valuable large-scale genotyping resource and facilitates the discovery of candidate genes associated with drought stress tolerance in rice.

Identification of genomic regions governing moisture and heat stress tolerance employing association mapping in rice (Oryza sativa L.)

BACKGROUND

Rice crop is damaged extremely by abiotic stress world-wide. The best approach to enhance drought tolerance in rice varieties is to identify and introgress yield QTLs with major effects. The Association mapping approach helps in the identification of genomic regions governing physiological, yield and yield attributes under moisture and heat stress conditions in diverse collections of crop germplasm, based on historic recombination events and linkage disequilibrium across the genome.

METHODS AND RESULTS

The association mapping panel of 110 rice germplasm lines exhibited significant variation for all the traits in both irrigated and moisture stress conditions. The extent of yield reduction ranged to 83% during rabi, 2018-19, 53% in rabi, 2019-20 and 68% in pooled analysis. The genotypes Badami, Badshabhog, Pankaj, Varalu, Vasundhara, Vivekdhan, Krishna and Minghui63 exhibited drought tolerance with least yield penalty under moisture stress conditions. The genotypes Konark, MTU3626, NLR33671, PR118 and Triguna exhibited minimal reduction in heat stress tolerance traits. Association mapping of germplasm using 37808 SNP markers detected a total of 10 major MTA (Marker-trait association) clusters distributed on chromosomes 1, 3, 4 and 11 through mixed linear model (MLM) governing multiple traits from individual data analysis which are consistent across the years and situations. The pooled data generated a total of five MTA clusters located on chromosome 6. In addition, several novel unique MTAs were also identified. Heat stress analysis generated a total of 23 MTAs distributed on chromosomes 1, 5, 6 and 11. Candidate gene analysis detected a total of 53 and 38 genes under individual and pooled data analysis for various yield and yield attributes under control and moisture stress conditions, respectively and a total of 11 candidate genes in heat stress Conditions.

CONCLUSION

The major and novel MTAs identified in the present investigation for various drought and heat tolerant traits can be utilized for breeding climate-resilient rice varieties. The candidate genes predicted for key MTAs are of great value to deploy into the rice breeding after functional characterization.

Wild soybean salt tolerance metabolic model: Assessment of storage protein mobilization in cotyledons and C/N balance in the hypocotyl/root axis

Salt stress has become one of the main factors limiting crop yield in recent years. The post-germinative growth is most sensitive to salt stress in soybean. In this study, cultivated and wild soybeans were used for an integrated metabonomics and transcriptomics analysis to determine whether wild soybean can resist salt stress by maintaining the mobilization of stored substances in cotyledons and the balance of carbon and nitrogen in the hypocotyl/root axis (HRA). Compared with wild soybean, the growth of cultivated soybean was significantly inhibited during the post-germinative growth period under salt stress. Integrating analysis found that the breakdown products of proteins, such as glutamate, glutamic acid, aspartic acid, and asparagine, increased significantly in wild soybean cotyledons. Asparagine synthase and fumarate hydratase genes and genes encoding HSP20 family proteins were specifically upregulated. In wild soybean HRA, levels of glutamic acid, aspartic acid, asparagine, citric acid, and succinic acid increased significantly, and the glutamate decarboxylase gene and the gene encoding carbonic anhydrase in nitrogen metabolism were significantly upregulated. The metabolic model indicated that wild soybean enhanced the decomposition of stored proteins and the transport of amino acids to the HRA in cotyledons and the GABA shunt to maintain carbon and nitrogen balance in the HRA to resist salt stress. This study provided a theoretical basis for cultivating salt-tolerant soybean varieties and opened opportunities for the development of sustainable agricultural practices.

Field Evaluation of Wheat Varieties Using Canopy Temperature Depression in Three Different Climatic Growing Seasons

During the breeding progress, screening excellent wheat varieties and lines takes lots of labor and time. Moreover, different climatic conditions will bring more complex and unpredictable situations. Therefore, the selection efficiency needs to be improved by applying the proper selection index. This study evaluates the capability of CTD as an index for evaluating wheat germplasm in field conditions and proposes a strategy for the proper and efficient application of CTD as an index in breeding programs. In this study, 186 bread wheat varieties were grown in the field and evaluated for three continuous years with varied climatic conditions: normal, spring freezing, and early drought climatic conditions. The CTD and photosynthetic parameters were investigated at three key growth stages, canopy structural traits at the early grain filling stage, and yield traits at maturity. The variations in CTD among varieties were the highest in normal conditions and lowest in spring freezing conditions. CTD at the three growing stages was significantly and positively correlated for each growing season, and CTD at the middle grain filling stage was most significantly correlated across the three growing seasons, suggesting that CTD at the middle grain filling stage might be more important for evaluation. CTD was greatly affected by photosynthetic and canopy structural traits, which varied in different climatic conditions. Plant height, peduncle length, and the distance of the flag leaf to the spike were negatively correlated with CTD at the middle grain filling stage in both normal and drought conditions but positively correlated with CTD at the three stages in spring freezing conditions. Flag leaf length was positively correlated with CTD at the three stages in normal conditions but negatively correlated with CTD at the heading and middle grain filling stages in spring freezing conditions. Further analysis showed that CTD could be an index for evaluating the photosynthetic and yield traits of wheat germplasm in different environments, with varied characteristics in different climatic conditions. In normal conditions, the varieties with higher CTDs at the early filling stage had higher photosynthetic capacities and higher yields; in drought conditions, the varieties with high CTDs had better photosynthetic capacities, but those with moderate CTD had higher yield, while in spring freezing conditions, there were no differences in yield and biomass among the CTD groups. In sum, CTD could be used as an index to screen wheat varieties in specific climatic conditions, especially in normal and drought conditions, for photosynthetic parameters and some yield traits.

A transcription factor TaMYB5 modulates leaf rolling in wheat

Leaf rolling is an important agronomic trait in wheat (Triticum aestivum L.). Moderate leaf rolling keeps leaves upright and maintains the relatively normal photosynthesis of plants under drought stress. However, the molecular mechanism of wheat leaf rolling remains unclear. Here, we identified a candidate gene TaMYB5-3A that regulates leaf rolling by using a genome-wide association study (GWAS) in a panel of 323 wheat accessions. Phenotype analysis indicated that the leaves of tamyb5 mutants were flatter than that of the wild type under drought condition. A nucleotide variation in the TaMYB5-3A coding region resulted in a substitution of Thr to Lys, which corresponds to two alleles SNP-3A-1 and SNP-3A-2. The leaf rolling index (LRI) of the SNP-3A-1 genotype was significantly lower than that of the SNP-3A-2 genotype. In addition, TaMYB5-3A alleles were associated with canopy temperature (CT) in multiple environments. The CT of the SNP-3A-1 genotype was lower than that of the SNP-3A-2 genotype. Gene expression analysis showed that TaMYB5-3A was mainly expressed in leaves and down-regulated by PEG and ABA treatment. TaMYB5 induces TaNRL1 gene expression through the direct binding to the AC cis-acting element of the promoter of the target gene, which was validated by EMSA (electrophoretic mobility shift assay). Our results revealed a crucial molecular mechanism in wheat leaf rolling and provided the theoretical basis and a gene resource for crop breeding.

Genome-Wide Association Mapping Reveals Novel Putative Gene Candidates Governing Reproductive Stage Heat Stress Tolerance in Rice

Temperature rise predicted for the future will severely affect rice productivity because the crop is highly sensitive to heat stress at the reproductive stage. Breeding tolerant varieties is an economically viable option to combat heat stress, for which the knowledge of target genomic regions associated with the reproductive stage heat stress tolerance (RSHT) is essential. A set of 192 rice genotypes of diverse origins were evaluated under natural field conditions through staggered sowings for RSHT using two surrogate traits, spikelet fertility and grain yield, which showed significant reduction under heat stress. These genotypes were genotyped using a 50 k SNP array, and the association analysis identified 10 quantitative trait nucleotides (QTNs) for grain yield, of which one QTN (qHTGY8.1) was consistent across the different models used. Only two out of 10 MTAs coincided with the previously reported QTLs, making the remaing eight novel. A total of 22 QTNs were observed for spikelet fertility, among which qHTSF5.1 was consistently found across three models. Of the QTNs identified, seven coincided with previous reports, while the remaining QTNs were new. The genes near the QTNs were found associated with the protein–protein interaction, protein ubiquitination, stress signal transduction, and so forth, qualifying them to be putative for RSHT. An in silico expression analysis revealed the predominant expression of genes identified for spikelet fertility in reproductive organs. Further validation of the biological relevance of QTNs in conferring heat stress tolerance will enable their utilization in improving the reproductive stage heat stress tolerance in rice.

Can biochemical traits bridge the gap between genomics and plant performance? A study in rice under drought

The possibility of introducing metabolic/biochemical phenotyping to complement genomics-based predictions in breeding pipelines has been considered for years. Here we examine to what extent and under what environmental conditions metabolic/biochemical traits can effectively contribute to understanding and predicting plant performance. In this study, multivariable statistical models based on flag leaf central metabolism and oxidative stress status were used to predict grain yield (GY) performance for 271 indica rice (Oryza sativa) accessions grown in the field under well-watered and reproductive stage drought conditions. The resulting models displayed significantly higher predictability than multivariable models based on genomic data for the prediction of GY under drought (Q2 = 0.54-0.56 versus 0.35) and for stress-induced GY loss (Q2 = 0.59-0.64 versus 0.03-0.06). Models based on the combined datasets showed predictabilities similar to metabolic/biochemical-based models alone. In contrast to genetic markers, models with enzyme activities and metabolite values also quantitatively integrated the effect of physiological differences such as plant height on GY. The models highlighted antioxidant enzymes of the ascorbate-glutathione cycle and a lipid oxidation stress marker as important predictors of rice GY stability under drought at the reproductive stage, and these stress-related variables were more predictive than leaf central metabolites. These findings provide evidence that metabolic/biochemical traits can integrate dynamic cellular and physiological responses to the environment and can help bridge the gap between the genome and the phenome of crops as predictors of GY performance under drought.

Advances in optical phenotyping of cereal crops

Optical sensors and sensing-based phenotyping techniques have become mainstream approaches in high-throughput phenotyping for improving trait selection and genetic gains in crops. We review recent progress and contemporary applications of optical sensing-based phenotyping (OSP) techniques in cereal crops and highlight optical sensing principles for spectral response and sensor specifications. Further, we group phenotypic traits determined by OSP into four categories - morphological, biochemical, physiological, and performance traits - and illustrate appropriate sensors for each extraction. In addition to the current status, we discuss the challenges of OSP and provide possible solutions. We propose that optical sensing-based traits need to be explored further, and that standardization of the language of phenotyping and worldwide collaboration between phenotyping researchers and other fields need to be established.

Breeding rice for a changing climate by improving adaptations to water saving technologies

Climate change is expected to increasingly affect rice production through rising temperatures and decreasing water availability. Unlike other crops, rice is a main contributor to greenhouse gas emissions due to methane emissions from flooded paddy fields. Climate change can therefore be addressed in two ways in rice: through making the crop more climate resilient and through changes in management practices that reduce methane emissions and thereby slow global warming. In this review, we focus on two water saving technologies that reduce the periods lowland rice will be grown under fully flooded conditions, thereby improving water use efficiency and reducing methane emissions. Rice breeding over the past decades has mostly focused on developing high-yielding varieties adapted to continuously flooded conditions where seedlings were raised in a nursery and transplanted into a puddled flooded soil. Shifting cultivation to direct-seeded rice or to introducing non-flooded periods as in alternate wetting and drying gives rise to new challenges which need to be addressed in rice breeding. New adaptive traits such as rapid uniform germination even under anaerobic conditions, seedling vigor, weed competitiveness, root plasticity, and moderate drought tolerance need to be bred into the current elite germplasm and to what extent this is being addressed through trait discovery, marker-assisted selection and population improvement are reviewed.

Nutritional improvement of cereal crops to combat hidden hunger during COVID-19 pandemic: Progress and prospects

COVID-19 has posed a severe challenge on food security by limiting access to food for the marginally placed population. While access to food is a challenge, access to nutritional food is a greater challenge to the population. The present-day foods are not sufficient to meet the nutritional requirements of the human body. In a pandemic condition, providing nutritious food to the population is imperative to ensure the health and well-being of humankind. Exploiting the existing biodiversity of crop species and deploying classical and modern tools to improve the nutritional potential of these species holds the key to addressing the above challenge. Breeding has been a classical tool of crop improvement that relied predominantly on genetic diversity. Collecting and conserving diverse germplasms and characterizing their diversity using molecular markers is essential to preserve diversity and use them in genetic improvement programs. These markers are also valuable for association mapping analyses to identify the genetic determinants of traits-of-interest in crop species. Association mapping identifies the quantitative trait loci (QTL) underlying the trait-of-interest by exploring marker-trait associations, and these QTLs can further be exploited for the genetic improvement of cultivated species through genomics-assisted breeding. Conventional breeding and genomics approaches are also being applied to develop biofortified cereal crops to reduce nutritional deficiencies in consumers. In this context, chapter explains the prerequisites for association mapping, population structure, genetic diversity, different approaches of performing association mapping to dissect nutritional traits, use the information for genomics-assisted breeding for nutrient-rich cereal crops, and application of genomics strategies in crop biofortification. These approaches will ensure food and nutrition security for all amidst the current COVID-19 crisis.

Optical Imaging Resources for Crop Phenotyping and Stress Detection

With a rapidly increasing population, diminishing resource availability, and variation in environment, there is a need to change agricultural production to deliver long-term food security. To deliver such change, we need crops that are productive and tolerant to different stress factors. The traditional methods of obtaining data for phenotyping under field conditions, e.g., for morphological traits such as canopy structure or physiological traits such as plant stress-related traits, are laborious and time-consuming. A variety of imaging tools in the visible, spectral, and thermal infrared ranges allow data collection for quantitative studies of complex traits and crop monitoring. These tools can be used on crop phenotyping and monitoring platforms for high-throughput assessment of traits in order to better understand plant stress responses and the physiological pathways underlying yield. The applications and brief review of these imaging techniques are described and discussed in this chapter.

A high-resolution genome-wide association study of the grain ionome and agronomic traits in rice Oryza sativa subsp. indica

This study presents a comprehensive study of the genetic bases controlling variation in the rice ionome employing genome-wide association studies (GWAS) with a diverse panel of indica accessions, each genotyped with 5.2 million markers. GWAS was performed for twelve elements including B, Ca, Co, Cu, Fe, K, Mg, Mn, Mo, Na, P, and Zn and four agronomic traits including days to 50% flowering, grain yield, plant height and thousand grain weight. GWAS identified 128 loci associated with the grain elements and 57 associated with the agronomic traits. There were sixteen co-localization regions containing QTL for two or more traits. Fourteen grain element quantitative trait loci were stable across growing environments, which can be strong candidates to be used in marker-assisted selection to improve the concentrations of nutritive elements in rice grain. Potential candidate genes were revealed including OsNAS3 linked to the locus that controls the variation of Zn and Co concentrations. The effects of starch synthesis and grain filling on multiple grain elements were elucidated through the likely involvement of OsSUS1 and OsGSSB1 genes. Overall, our study provides crucial insights into the genetic basis of ionomic variations in rice and will facilitate improvement in breeding for trace mineral content.

Improving drought tolerance in rice: Ensuring food security through multi-dimensional approaches

Drought has been highly prevalent around the world especially in Sub-Saharan Africa and South-East Asian countries. Consistent climatic instabilities and unpredictable rainfall patterns are further worsening the situation. Rice is a C₃ staple cereal and an important food crop for the majority of the world's population and drought stress is one of the major growth retarding threats for rice that slashes down grain quality and yield. Drought deteriorates rice productivity and induces various acclimation responses that aids in stress mitigation. However, the complexity of traits associated with drought tolerance has made the understanding of drought stress-induced responses in rice a challenging process. An integrative understanding based on physiological adaptations, omics, transgenic and molecular breeding approaches successively backed up to developing drought stress-tolerant rice. The review represents a step forward to develop drought-resilient rice plants by exploiting the knowledge that collaborates with omics-based developments with integrative efforts to ensure the compilation of all the possible strategies undertaken to develop drought stress-tolerant rice.

Development and Validation of Methodology for Estimating Potato Canopy Structure for Field Crop Phenotyping and Improved Breeding

Traditional phenotyping techniques have long been a bottleneck in breeding programs and genotype- phenotype association studies in potato, as these methods are labor-intensive and time consuming. In addition, depending on the trait measured and metric adopted, they suffer from varying degrees of user bias and inaccuracy, and hence these challenges have effectively prevented the execution of large-scale population-based field studies. This is true not only for commercial traits (e.g., yield, tuber size, and shape), but also for traits strongly associated with plant performance (e.g., canopy development, canopy architecture, and growth rates). This study demonstrates how the use of point cloud data obtained from low-cost UAV imaging can be used to create 3D surface models of the plant canopy, from which detailed and accurate data on plant height and its distribution, canopy ground cover and canopy volume can be obtained over the growing season. Comparison of the canopy datasets at different temporal points enabled the identification of distinct patterns of canopy development, including different patterns of growth, plant lodging, maturity and senescence. Three varieties are presented as exemplars. Variety Nadine presented the growth pattern of an early maturing variety, showing rapid initial growth followed by rapid onset of senescence and plant death. Varieties Bonnie and Bounty presented the pattern of intermediate to late maturing varieties, with Bonnie also showing early canopy lodging. The methodological approach used in this study may alleviate one of the current bottlenecks in the study of plant development, paving the way for an expansion in the scale of future genotype-phenotype association studies.

Water relations responses of the pea (Pisum sativum L.) mutant SGECdt to mercury

Mercury (Hg) is one of the most toxic heavy metals and has multiple impacts on plant growth and physiology, including disturbances of plant water status. The impact of Hg on water relations was assessed by exposing the unique Hg-sensitive pea (Pisum sativum L.) mutant SGECdt and its wild-type (WT) line SGE in hydroponic culture. When the plants were grown in the presence of 1 or 2 µM HgCl2 for 11 days, the SGECdt mutant had lower whole plant transpiration rate and increased leaf temperature, indicating stomatal closure. Shoot removal of Hg-untreated plants resulted in greater root-pressure induced xylem sap flow in the SGECdt mutant than WT plants. Treating these plants with 50 µM HgCl2 (an inhibitor of aquaporins) for 1 h decreased xylem sap flow of both genotypes by about 5 times and eliminated differences between WT and mutant. Adding 1 mM dithiothreitol (the reducing thiol reagent used for opening aquaporins) to the nutrient solution of Hg-treated plants partially restored xylem sap flow in SGECdt roots only, suggesting genotypic differences in aquaporin function. Thus root water uptake is important in mediating sensitivity of SGECdt to toxic Hg.